Causal AI Simulation Tool for Reducing Internal Corrosion Damage in Hazardous Liquid Pipelines

Internal corrosion is a major challenge for hazardous liquid pipeline operators and can be difficult to detect. Even when corrosion is identified, it’s hard to determine the cause.. Early identification of corrosion coupled with a clear understanding of the corrosion mechanism and the most effective way to slow corrosion growth can prevent damage to assets, the environment, and human safety while saving pipeline operators money. No data or quantitative risk assessment tool reliably provides this information today. Senslytics is developing CorroSim: an AI corrosion simulation application using its proprietary causal Intuition AI technology, that can understand and model influencers of internal corrosion behavior, differentiate aerobic vs. anaerobic microbial-influenced corrosion, and extend interpretation to new situations. Upon completion of phase II, this product would enable engineers to perform simulations to determine the most effective method for addressing internal corrosion. The proposed solution uses a hybrid AI approach that combines data with subject matter expert knowledge codified into the model. It produces reliable, definitive interpretations while overcoming the challenges machine learning runs into with limited data availability. The benefits of the proposed solution to pipeline operators include reducing internal corrosion and optimizing corrosion management spending, ultimately minimizing environmental and human safety risks.